Machine Learning Infrastructure Tech Lead
Tasks
- Build tooling and abstractions for ML production
- Build training and inference stack
- Design multi node multi GPU training systems
- Develop infrastructure benchmarks
- Evaluate and apply training and inference advancements
- Improve GPU utilization latency throughput reliability observability cost efficiency
- Lead technical direction and architecture decisions
- Optimize model serving kernels and runtimes
- Own ML infrastructure roadmap
- Perform design reviews and mentorship
Perks/Benefits
- Commuter reimbursement
- Daily lunch
- Dental insurance
- Health and wellness budget
- Health insurance
- Parental leave
- Unlimited PTO
- Vision insurance
Skills/Tech-stack
Batching | Benchmarking | CUDA | Distributed Systems | GPU Utilization | Inference Optimization | Kubernetes | Latency optimization | Model Serving | Observability | PyTorch | Python | Ray | Scheduling | TensorRT-LLM | Throughput Optimization | Training Optimization | Triton
Education
N/A
Regions
Countries
States
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